Understanding the YouTube Partners and Their Data: Measurement and Analysis
User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the use...
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Veröffentlicht in: | China communications 2014-12, Vol.11 (12), p.26-34 |
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creator | Cheng, Xu Mehrdad, Fatourechi Ma, Xiaoqiang Zhang, Cong Liu, Jiangchuan |
description | User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the users' watching and sharing activities.The substantial benefit is to further augment its service and monetize more videos,which is crucial to both YouTube and its partners,as well as to other providers of relevant services.In this paper,our main contribution is to analyze the massive amounts of video data from a YouTube partner's view.We make effective use of Insight,a new analytics service of YouTube that offers simple data analysis for partners.To provide the practical guidance from the raw Insight data,we enable more complex investigations for the inherent features that affect the popularity of the videos.Our findings facilitate YouTube partners to re-design current video publishing strategies,having more opportunities to attract more views. |
doi_str_mv | 10.1109/CC.2014.7019837 |
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Mehrdad, Fatourechi ; Ma, Xiaoqiang ; Zhang, Cong ; Liu, Jiangchuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2333-78f7a2872db930d8710402efb60f6d6e95923ef451a00259ab8cfd60f55d3ef53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Behavioral science</topic><topic>Big data</topic><topic>Games</topic><topic>Motion pictures</topic><topic>user engagement</topic><topic>Video communication</topic><topic>video popularity</topic><topic>viewing behaviour</topic><topic>Watches</topic><topic>YouTube</topic><topic>YouTube partners</topic><topic>供应商</topic><topic>内容提供商</topic><topic>分析服务</topic><topic>合作伙伴</topic><topic>数据分析</topic><topic>测量</topic><topic>用户</topic><topic>视频数据</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cheng, Xu</creatorcontrib><creatorcontrib>Mehrdad, Fatourechi</creatorcontrib><creatorcontrib>Ma, Xiaoqiang</creatorcontrib><creatorcontrib>Zhang, Cong</creatorcontrib><creatorcontrib>Liu, Jiangchuan</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>China communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cheng, Xu</au><au>Mehrdad, Fatourechi</au><au>Ma, Xiaoqiang</au><au>Zhang, Cong</au><au>Liu, Jiangchuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Understanding the YouTube Partners and Their Data: Measurement and Analysis</atitle><jtitle>China communications</jtitle><stitle>ChinaComm</stitle><addtitle>China Communications</addtitle><date>2014-12-01</date><risdate>2014</risdate><volume>11</volume><issue>12</issue><spage>26</spage><epage>34</epage><pages>26-34</pages><issn>1673-5447</issn><coden>CCHOBE</coden><abstract>User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the users' watching and sharing activities.The substantial benefit is to further augment its service and monetize more videos,which is crucial to both YouTube and its partners,as well as to other providers of relevant services.In this paper,our main contribution is to analyze the massive amounts of video data from a YouTube partner's view.We make effective use of Insight,a new analytics service of YouTube that offers simple data analysis for partners.To provide the practical guidance from the raw Insight data,we enable more complex investigations for the inherent features that affect the popularity of the videos.Our findings facilitate YouTube partners to re-design current video publishing strategies,having more opportunities to attract more views.</abstract><pub>China Institute of Communications</pub><doi>10.1109/CC.2014.7019837</doi><tpages>9</tpages></addata></record> |
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source | IEEE Electronic Library (IEL) |
subjects | Behavioral science Big data Games Motion pictures user engagement Video communication video popularity viewing behaviour Watches YouTube YouTube partners 供应商 内容提供商 分析服务 合作伙伴 数据分析 测量 用户 视频数据 |
title | Understanding the YouTube Partners and Their Data: Measurement and Analysis |
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